We Tell You Whether a Protein Is Druggable — and How
First-principles physics. No training data. No pattern matching. From atomic structure to druggability assessment in seconds. The platform discriminates — it does not just score.
First-Principles Structural Physics
The engine processes any protein through a physics-based pipeline. Local Potency Density fields are computed from atomic coordinates using proprietary constants — no training data, no machine learning, no pattern matching.
LPD Field Computation
Local Potency Density field computed from proprietary atomic constants. Every atom contributes to the 3D potency landscape.
Peak & Valley Discovery
Automated scanning identifies peaks (high-potency binding hotspots) and valleys (cryptic sites hidden from conventional tools).
Basin Characterization
Deep pocket analysis: enclosure, depth, volume, stability, chemistry balance, and structural coherence scoring.
Binding Lock Analysis
Cross-reference with known ligand binding sites. Validate computational predictions against experimental evidence.
Druggability Assessment
Global druggability score from structural evidence. Clear discrimination: druggable, difficult, or undruggable.
Discovery Coordinates
Precise 3D coordinates for every binding site. Actionable output for experimental validation and drug design.
The Platform Produces Three Distinct Outcomes
Not just a score — a decision. Each case below represents a hard-target protein that conventional computational tools cannot correctly classify.
β-Catenin
YES, BUT CAREFULLY5 STRUCTURESFive conformational states analyzed (AlphaFold, BCL9/TCF4, hTcf-4, Compound 6, Axin). Scores 65–88/100. Recurring 299–312 Da compact inhibitor hypothesis across all states. Strong coherence. The hardest positive in oncology — and the engine says yes.
MYC
NO, CLEARLYScore 12/100. Top pocket 0/100. Non-small-molecule constrained. Consistent with 30 years of failed MYC drug programs. The engine correctly says no.
TDP-43
THIS DOMAIN, NOT THAT ONERRM1 domain is the strongest small-molecule-compatible region. Other domains are weaker or alternative-modality constrained. The engine prioritizes where to invest, not just whether.
p53 Y220C
RESCUED POCKETApo mutant 93/100, ligand-bound with rezatapopt 83/100. Same 338 Da primary lead in both states (rezatapopt is ~360 Da). The engine recovers the clinically validated Y220C pocket.
Why This Is Not Another Docking Tool
| Dimension | Conventional Tools | Ashebo Method |
|---|---|---|
| Foundation | Geometric heuristics or ML | First-principles atomic physics |
| Training data | Thousands of known complexes | Based on new physics concept that also solved the many-body problem |
| Output | Pocket score | 6-layer stack: score → pocket → biology → chemistry → therapy → molecule |
| Hard targets | False positives / false negatives | Discriminates: yes / no / where |
| Novel proteins | Degrades without training data | Works on any atomic structure |
| Multi-state | Single structure | Cross-state validated (5 β-catenin conformations) |
Ready to Validate Your Target?
We run your protein through the full 6-layer decision stack and deliver a comprehensive report — structural assessment, chemistry strategy, and molecular hypotheses — typically within 48 hours.